MATHEMATICAL MODELING OF BIOLOGICAL NETWORK GOVERNING C ELEGANS VULVAL INDUCTI

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 线虫外阴发育是动物器官发生的典范，具有广泛的实验数据。在外阴诱导过程中，六个多能外阴前体细胞(VPC)中的每一个都承担着三种命运(1？、2？、3？)中的一种。VPC命运的精确形成受细胞间信号、细胞内信号转导和转录调控网络的控制。为这个网络构建数学模型将使假设生成、生物机制发现和系统行为分析成为可能。可以开发一个数学模型来对控制VPC 1？-2？-3图案形成过程的生物网络进行建模。提出用动态贝叶斯网络对网络组件间的因果关系进行建模。该问题是一个计算密集型问题，我们还提出了采用并行算法来提高计算速度。数学建模的实现将用C/C++和MPI。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. C. elegans vulval development is a paradigmatic example of animal organogenesis with extensive experimental data. During vulval induction, each of the six multipotent vulval precursor cells (VPCs) commits to one of three fates (1¿, 2¿, 3¿). The precise 1¿-2¿-3¿ formation of VPC fates is controlled by a network of intercellular signaling, intracellular signal transduction, and transcriptional regulation. The construction of mathematical models for this network will enable hypothesis generation, biological mechanism discovery, and system behavior analysis. A mathematical model can be developed to model the biological network that governs the VPC 1¿-2¿-3¿ pattern formation process. We proposed to apply dynamic Bayesian network to model the causal relationship among network components. The problem is computationally intensive, we also propose to implement parallel algorithm to speed up the computation. The implementation of the mathematical modeling will be in C/C++ and MPI.